Hello,

l have dataset got from numpy. l would like to apply transform.Normalize

```
normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225])
```

which is basically applied on ImageFolder as follow :

```
train_loader = torch.utils.data.DataLoader(
datasets.ImageFolder(traindir, transforms.Compose([
transforms.RandomSizedCrop(224),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
normalize,
])),
```

However l have numpy dataset so l have access to my dataset as follow :

```
data_train = torch.from_numpy(data_train).expand(-1,3,-1,-1)
labels_train=torch.from_numpy(output_le[:len(labels_train)])
train_data = torch.utils.data.TensorDataset(data_train.float(), labels_train)
train_loader = torch.utils.data.DataLoader(
train_data, batch_size=args.batch_size, shuffle=(train_sampler is None),
num_workers=args.workers, pin_memory=True, sampler=train_sampler)
```

How can l apply

```
normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225])
```

In this case ?

Thank you,